ETL & Visualisations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f728de34",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MultipleLocator, LogLocator\n",
    "\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "989ec64d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('./section-3-event-logs-template1.xlsx', engine='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9edb7574",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>event_uuid</th>\n",
       "      <th>user_uuid</th>\n",
       "      <th>event_time</th>\n",
       "      <th>device_type</th>\n",
       "      <th>session_uuid</th>\n",
       "      <th>user_neighborhood</th>\n",
       "      <th>event_page</th>\n",
       "      <th>event_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>ios</td>\n",
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       "      <td>Manhattan</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>ios</td>\n",
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       "      <td>book_page</td>\n",
       "      <td>choose_car</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>driver_page</td>\n",
       "      <td>choose_car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>a4ff8e2c-2701-4a32-9029-bdf6efc155c5</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
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       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:36:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>search</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>4676fca7-17c6-4999-99bf-dafbd851c0f9</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:37:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>splash_page</td>\n",
       "      <td>choose_car</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>41b4f6b1-cc14-4c77-a520-50c1cb9cd592</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:37:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>open</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>3808dca1-c80b-4ff7-96e5-b545d6c05c08</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:38:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>open</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>73b945e9-691e-4e63-aa4d-da2f74599388</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-12 06:27:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>8a08005b-7e74-4664-b25d-9e29d8316d71</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>splash_page</td>\n",
       "      <td>search</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>a070700c-8bd9-4b5a-9325-e029fda604c7</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-12 06:28:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>8a08005b-7e74-4664-b25d-9e29d8316d71</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>choose_car</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Unnamed: 0                            event_uuid  \\\n",
       "0           0  b9e9489e-1218-4715-b42e-604e3745db07   \n",
       "1           1  d7dca4a7-c4d0-4b50-b6fb-8c1429002b62   \n",
       "2           2  cf2d094a-2898-4547-9e52-23a8fc9fc459   \n",
       "3           3  a4ff8e2c-2701-4a32-9029-bdf6efc155c5   \n",
       "4           4  04a6ac8f-4535-42e9-b84c-6940fa491ee5   \n",
       "5           5  4676fca7-17c6-4999-99bf-dafbd851c0f9   \n",
       "6           6  41b4f6b1-cc14-4c77-a520-50c1cb9cd592   \n",
       "7           7  3808dca1-c80b-4ff7-96e5-b545d6c05c08   \n",
       "8           8  73b945e9-691e-4e63-aa4d-da2f74599388   \n",
       "9           9  a070700c-8bd9-4b5a-9325-e029fda604c7   \n",
       "\n",
       "                              user_uuid          event_time device_type  \\\n",
       "0  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:34:00         ios   \n",
       "1  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:35:00         ios   \n",
       "2  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:36:00         ios   \n",
       "3  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:36:00         ios   \n",
       "4  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:36:00         ios   \n",
       "5  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:37:00         ios   \n",
       "6  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:37:00         ios   \n",
       "7  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:38:00         ios   \n",
       "8  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-12 06:27:00         ios   \n",
       "9  8191a8b8-9445-4661-9500-2bed275576f6 2019-10-12 06:28:00         ios   \n",
       "\n",
       "                           session_uuid user_neighborhood   event_page  \\\n",
       "0  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan  search_page   \n",
       "1  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "2  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan  driver_page   \n",
       "3  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "4  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "5  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan  splash_page   \n",
       "6  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "7  2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "8  8a08005b-7e74-4664-b25d-9e29d8316d71         Manhattan  splash_page   \n",
       "9  8a08005b-7e74-4664-b25d-9e29d8316d71         Manhattan    book_page   \n",
       "\n",
       "   event_type  \n",
       "0  choose_car  \n",
       "1  choose_car  \n",
       "2  choose_car  \n",
       "3      search  \n",
       "4      search  \n",
       "5  choose_car  \n",
       "6        open  \n",
       "7        open  \n",
       "8      search  \n",
       "9  choose_car  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e196d8c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124980 entries, 0 to 124979\n",
      "Data columns (total 9 columns):\n",
      " #   Column             Non-Null Count   Dtype         \n",
      "---  ------             --------------   -----         \n",
      " 0   Unnamed: 0         124980 non-null  int64         \n",
      " 1   event_uuid         124980 non-null  object        \n",
      " 2   user_uuid          124980 non-null  object        \n",
      " 3   event_time         124980 non-null  datetime64[ns]\n",
      " 4   device_type        124980 non-null  object        \n",
      " 5   session_uuid       124980 non-null  object        \n",
      " 6   user_neighborhood  124980 non-null  object        \n",
      " 7   event_page         124980 non-null  object        \n",
      " 8   event_type         124980 non-null  object        \n",
      "dtypes: datetime64[ns](1), int64(1), object(7)\n",
      "memory usage: 8.6+ MB\n"
     ]
    }
   ],
   "source": [
    "#verifying if the index of event_time is a datetime format. \n",
    "\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7178f27a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['month'] = df['event_time'].dt.month\n",
    "df['day']= df['event_time'].dt.day\n",
    "df['hour']= df['event_time'].dt.hour\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "31a28b69",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124980 entries, 0 to 124979\n",
      "Data columns (total 12 columns):\n",
      " #   Column             Non-Null Count   Dtype         \n",
      "---  ------             --------------   -----         \n",
      " 0   Unnamed: 0         124980 non-null  int64         \n",
      " 1   event_uuid         124980 non-null  object        \n",
      " 2   user_uuid          124980 non-null  object        \n",
      " 3   event_time         124980 non-null  datetime64[ns]\n",
      " 4   device_type        124980 non-null  object        \n",
      " 5   session_uuid       124980 non-null  object        \n",
      " 6   user_neighborhood  124980 non-null  object        \n",
      " 7   event_page         124980 non-null  object        \n",
      " 8   event_type         124980 non-null  object        \n",
      " 9   month              124980 non-null  int64         \n",
      " 10  day                124980 non-null  int64         \n",
      " 11  hour               124980 non-null  int64         \n",
      "dtypes: datetime64[ns](1), int64(4), object(7)\n",
      "memory usage: 11.4+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e92c9a97",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>event_uuid</th>\n",
       "      <th>user_uuid</th>\n",
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       "      <th>device_type</th>\n",
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       "      <th>user_neighborhood</th>\n",
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       "      <th>40952</th>\n",
       "      <td>40952</td>\n",
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       "      <td>faeb8201-f8df-488f-9568-e700a7761ca6</td>\n",
       "      <td>2019-10-05 21:51:00</td>\n",
       "      <td>mobile_web</td>\n",
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       "      <td>Manhattan</td>\n",
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       "      <td>5</td>\n",
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       "    <tr>\n",
       "      <th>29725</th>\n",
       "      <td>29725</td>\n",
       "      <td>66559a31-df9c-4277-8164-6b3ceadbf550</td>\n",
       "      <td>ceb38a9c-e914-4560-a0d3-3a52a6d2f3fd</td>\n",
       "      <td>2019-10-09 20:17:00</td>\n",
       "      <td>android</td>\n",
       "      <td>993ed62e-8cc3-4f6b-9d83-62640e4b070f</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>search_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111483</th>\n",
       "      <td>111483</td>\n",
       "      <td>f573f287-2ec2-4b74-a653-0b68087e527d</td>\n",
       "      <td>81fba0d3-4104-4a99-ad8f-e4c833454111</td>\n",
       "      <td>2019-10-09 15:02:00</td>\n",
       "      <td>mobile_web</td>\n",
       "      <td>754f663e-5fca-42a7-aeeb-14147d40d745</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>splash_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0                            event_uuid  \\\n",
       "40952        40952  be794eb5-11e5-4d59-b261-7b4f480fe5f1   \n",
       "29725        29725  66559a31-df9c-4277-8164-6b3ceadbf550   \n",
       "111483      111483  f573f287-2ec2-4b74-a653-0b68087e527d   \n",
       "\n",
       "                                   user_uuid          event_time device_type  \\\n",
       "40952   faeb8201-f8df-488f-9568-e700a7761ca6 2019-10-05 21:51:00  mobile_web   \n",
       "29725   ceb38a9c-e914-4560-a0d3-3a52a6d2f3fd 2019-10-09 20:17:00     android   \n",
       "111483  81fba0d3-4104-4a99-ad8f-e4c833454111 2019-10-09 15:02:00  mobile_web   \n",
       "\n",
       "                                session_uuid user_neighborhood   event_page  \\\n",
       "40952   4e3ddaf8-c7aa-4daf-9044-910d444cc12d         Manhattan    book_page   \n",
       "29725   993ed62e-8cc3-4f6b-9d83-62640e4b070f         Manhattan  search_page   \n",
       "111483  754f663e-5fca-42a7-aeeb-14147d40d745         Manhattan  splash_page   \n",
       "\n",
       "       event_type  month  day  hour  \n",
       "40952        open     10    5    21  \n",
       "29725        open     10    9    20  \n",
       "111483       open     10    9    15  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b6a61c90",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Total of Events plotted by the day', size=16, y=0.95, weight='bold')\n",
    "\n",
    "df.groupby(['day'])['event_uuid'].count().plot(ax=ax,logy=True)\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('Log (COUNT) ', fontsize=16)\n",
    "ax.tick_params(axis ='x', which ='both', length = 0)\n",
    "\n",
    "ax.set_xlim(6, 11)\n",
    "y_major=MultipleLocator(1000)\n",
    "ax.yaxis.set_major_locator(y_major)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "688be95d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>event_uuid</th>\n",
       "      <th>user_uuid</th>\n",
       "      <th>event_time</th>\n",
       "      <th>device_type</th>\n",
       "      <th>session_uuid</th>\n",
       "      <th>user_neighborhood</th>\n",
       "      <th>event_page</th>\n",
       "      <th>event_type</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>hour</th>\n",
       "      <th>Time</th>\n",
       "      <th>Date</th>\n",
       "      <th>time</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>b9e9489e-1218-4715-b42e-604e3745db07</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:34:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>search_page</td>\n",
       "      <td>choose_car</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>05:34:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>05:34:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>d7dca4a7-c4d0-4b50-b6fb-8c1429002b62</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:35:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>choose_car</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>05:35:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>05:35:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>cf2d094a-2898-4547-9e52-23a8fc9fc459</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:36:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>driver_page</td>\n",
       "      <td>choose_car</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>05:36:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>05:36:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>a4ff8e2c-2701-4a32-9029-bdf6efc155c5</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:36:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>search</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>05:36:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>05:36:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>04a6ac8f-4535-42e9-b84c-6940fa491ee5</td>\n",
       "      <td>8191a8b8-9445-4661-9500-2bed275576f6</td>\n",
       "      <td>2019-10-06 05:36:00</td>\n",
       "      <td>ios</td>\n",
       "      <td>2d7b8da3-573a-447f-9964-acf32526b1db</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>book_page</td>\n",
       "      <td>search</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>05:36:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>05:36:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124975</th>\n",
       "      <td>124975</td>\n",
       "      <td>2080cc6a-861b-4253-9b2b-a617a146d3e2</td>\n",
       "      <td>71ade47d-d1a9-4dae-bf21-bb77291b35ed</td>\n",
       "      <td>2019-10-06 04:52:00</td>\n",
       "      <td>mobile_web</td>\n",
       "      <td>ef43011b-1525-451f-985f-90beece2f643</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>driver_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>04:52:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>04:52:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124976</th>\n",
       "      <td>124976</td>\n",
       "      <td>ac05e7c8-81d3-4401-a37e-2b0b194971fb</td>\n",
       "      <td>71ade47d-d1a9-4dae-bf21-bb77291b35ed</td>\n",
       "      <td>2019-10-06 04:53:00</td>\n",
       "      <td>mobile_web</td>\n",
       "      <td>ef43011b-1525-451f-985f-90beece2f643</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>search_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>04:53:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>04:53:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124977</th>\n",
       "      <td>124977</td>\n",
       "      <td>4ef00123-7c37-42bb-995e-c6dbfa090671</td>\n",
       "      <td>71ade47d-d1a9-4dae-bf21-bb77291b35ed</td>\n",
       "      <td>2019-10-06 04:53:00</td>\n",
       "      <td>mobile_web</td>\n",
       "      <td>ef43011b-1525-451f-985f-90beece2f643</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>driver_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>04:53:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>04:53:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124978</th>\n",
       "      <td>124978</td>\n",
       "      <td>f2050c51-6652-4299-bc3d-35ff402980c2</td>\n",
       "      <td>71ade47d-d1a9-4dae-bf21-bb77291b35ed</td>\n",
       "      <td>2019-10-06 04:54:00</td>\n",
       "      <td>mobile_web</td>\n",
       "      <td>ef43011b-1525-451f-985f-90beece2f643</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>search_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>04:54:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>04:54:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124979</th>\n",
       "      <td>124979</td>\n",
       "      <td>12bd28e7-7024-4169-a29f-44dc4f293e17</td>\n",
       "      <td>71ade47d-d1a9-4dae-bf21-bb77291b35ed</td>\n",
       "      <td>2019-10-06 04:55:00</td>\n",
       "      <td>mobile_web</td>\n",
       "      <td>ef43011b-1525-451f-985f-90beece2f643</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>search_page</td>\n",
       "      <td>open</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>04:55:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "      <td>04:55:00</td>\n",
       "      <td>2019-10-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124980 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Unnamed: 0                            event_uuid  \\\n",
       "0                0  b9e9489e-1218-4715-b42e-604e3745db07   \n",
       "1                1  d7dca4a7-c4d0-4b50-b6fb-8c1429002b62   \n",
       "2                2  cf2d094a-2898-4547-9e52-23a8fc9fc459   \n",
       "3                3  a4ff8e2c-2701-4a32-9029-bdf6efc155c5   \n",
       "4                4  04a6ac8f-4535-42e9-b84c-6940fa491ee5   \n",
       "...            ...                                   ...   \n",
       "124975      124975  2080cc6a-861b-4253-9b2b-a617a146d3e2   \n",
       "124976      124976  ac05e7c8-81d3-4401-a37e-2b0b194971fb   \n",
       "124977      124977  4ef00123-7c37-42bb-995e-c6dbfa090671   \n",
       "124978      124978  f2050c51-6652-4299-bc3d-35ff402980c2   \n",
       "124979      124979  12bd28e7-7024-4169-a29f-44dc4f293e17   \n",
       "\n",
       "                                   user_uuid          event_time device_type  \\\n",
       "0       8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:34:00         ios   \n",
       "1       8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:35:00         ios   \n",
       "2       8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:36:00         ios   \n",
       "3       8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:36:00         ios   \n",
       "4       8191a8b8-9445-4661-9500-2bed275576f6 2019-10-06 05:36:00         ios   \n",
       "...                                      ...                 ...         ...   \n",
       "124975  71ade47d-d1a9-4dae-bf21-bb77291b35ed 2019-10-06 04:52:00  mobile_web   \n",
       "124976  71ade47d-d1a9-4dae-bf21-bb77291b35ed 2019-10-06 04:53:00  mobile_web   \n",
       "124977  71ade47d-d1a9-4dae-bf21-bb77291b35ed 2019-10-06 04:53:00  mobile_web   \n",
       "124978  71ade47d-d1a9-4dae-bf21-bb77291b35ed 2019-10-06 04:54:00  mobile_web   \n",
       "124979  71ade47d-d1a9-4dae-bf21-bb77291b35ed 2019-10-06 04:55:00  mobile_web   \n",
       "\n",
       "                                session_uuid user_neighborhood   event_page  \\\n",
       "0       2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan  search_page   \n",
       "1       2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "2       2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan  driver_page   \n",
       "3       2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "4       2d7b8da3-573a-447f-9964-acf32526b1db         Manhattan    book_page   \n",
       "...                                      ...               ...          ...   \n",
       "124975  ef43011b-1525-451f-985f-90beece2f643         Manhattan  driver_page   \n",
       "124976  ef43011b-1525-451f-985f-90beece2f643         Manhattan  search_page   \n",
       "124977  ef43011b-1525-451f-985f-90beece2f643         Manhattan  driver_page   \n",
       "124978  ef43011b-1525-451f-985f-90beece2f643         Manhattan  search_page   \n",
       "124979  ef43011b-1525-451f-985f-90beece2f643         Manhattan  search_page   \n",
       "\n",
       "        event_type  month  day  hour      Time        Date      time  \\\n",
       "0       choose_car     10    6     5  05:34:00  2019-10-06  05:34:00   \n",
       "1       choose_car     10    6     5  05:35:00  2019-10-06  05:35:00   \n",
       "2       choose_car     10    6     5  05:36:00  2019-10-06  05:36:00   \n",
       "3           search     10    6     5  05:36:00  2019-10-06  05:36:00   \n",
       "4           search     10    6     5  05:36:00  2019-10-06  05:36:00   \n",
       "...            ...    ...  ...   ...       ...         ...       ...   \n",
       "124975        open     10    6     4  04:52:00  2019-10-06  04:52:00   \n",
       "124976        open     10    6     4  04:53:00  2019-10-06  04:53:00   \n",
       "124977        open     10    6     4  04:53:00  2019-10-06  04:53:00   \n",
       "124978        open     10    6     4  04:54:00  2019-10-06  04:54:00   \n",
       "124979        open     10    6     4  04:55:00  2019-10-06  04:55:00   \n",
       "\n",
       "              date  \n",
       "0       2019-10-06  \n",
       "1       2019-10-06  \n",
       "2       2019-10-06  \n",
       "3       2019-10-06  \n",
       "4       2019-10-06  \n",
       "...            ...  \n",
       "124975  2019-10-06  \n",
       "124976  2019-10-06  \n",
       "124977  2019-10-06  \n",
       "124978  2019-10-06  \n",
       "124979  2019-10-06  \n",
       "\n",
       "[124980 rows x 16 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "df['time'],df['date']= df['event_time'].apply(lambda x:x.time()), df['event_time'].apply(lambda x:x.date())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dcaa6138",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2019-10-05     9891\n",
       "2019-10-06    18056\n",
       "2019-10-07    18202\n",
       "2019-10-08    17963\n",
       "2019-10-09    17600\n",
       "2019-10-10    17694\n",
       "2019-10-11    17595\n",
       "2019-10-12     7979\n",
       "Name: event_uuid, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['date'])['event_uuid'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "3be194d4",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'Series' object has no attribute 'info'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-43-cef9eb48aab7>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mdf_n\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_n\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'date'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'event_uuid'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mdf_n\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0mdf_n\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/anaconda3/envs/newenv/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   5463\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5464\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5465\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5466\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5467\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'Series' object has no attribute 'info'"
     ]
    }
   ],
   "source": [
    "df['date']=  pd.to_datetime(df['date'])\n",
    "df_n = df[['event_uuid', 'date', 'time', 'user_uuid']]\n",
    "df_n = df_n.set_index('date')\n",
    "df_n = df_n.groupby(['date'])['event_uuid'].count()\n",
    "\n",
    "df_n.info()\n",
    "df_n.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "bb44f995",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'datetime.datetime'>\n",
      "<class 'datetime.datetime'>\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_date = datetime(2019,10,1)\n",
    "end_date = datetime(2019,11,1)\n",
    "print(type(start_date))\n",
    "print(type(end_date))\n",
    "df_n[(start_date <= df_n.index) & (df_n.index <= end_date)].plot(grid=True)\n",
    "\n",
    "df_n.to_csv('./testontableau')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f6d18686",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'statmodels'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-45-3fffb6c39489>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#additive decomposition model https://towardsdatascience.com/analyzing-time-series-data-in-pandas-be3887fdd621\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mstatmodels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapi\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msm\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'statmodels'"
     ]
    }
   ],
   "source": [
    "#additive decomposition model https://towardsdatascience.com/analyzing-time-series-data-in-pandas-be3887fdd621\n",
    "\n",
    "import statmodels.api as sm\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "576120f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='hour'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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e5xxrfZI+eRGPd5S/f243f3LpIuaEtK5PB70eL599eDP72j56U51Xmk9dlYO6agd11UXUVTkoCfQlS3eh1erh/MHZNfzry/t4fMsR/va6ZWGvUR9pcLkpzMka2y4dq6pAwWFzzyBLZidnd5wGEXWCfW19DExQZBgqHdvB/37/cR7fcoSakny+vG6iZgjJ5x318Se/2E5ju5sHP3s2eTYru471sOtYDx8c6z6h+211cR4rgkGl2h9gygqm98aSCMFq9YmCSFlBDlcFEux/8bEl5GbP7CVPYwzNPZ6xgr9oBXtmTbQbMlJjrU90JqJSZfvhbmDypDqEtINPo6r1DftcAOxpTp9T9owx/PUzO9nUcJx/+fRKrq6bDcAlp5WPXdM9MMzu5l52Huth57Eedh/r4cXdHyWla0vzeeyONdSWxVaElgjBavVwy1lBt66ZywsftPDS7lZuPHNm50Ye/v0BvrO+nr+9bhl3Xjg/6s9vbHdzccjPRKwqCnOwSHL7Z2kQUSd479DkRYZBjrxsrBZJm5mIMYaNe/1BZFdz+rS2+eHrDTy17ShfvXwxN62eE/aa4nwbaxeVsXZR2dhjPYNe9jT3sutYD999aS//teUwf/3xpcka9pTaej0U5mRhz5n4LeT8BaXMCyTYZ3IQaekZ5Puvfki+zco/Pr+Hghwrf3jO3Ig/v9fjxdU3NO18CECW1cKsotyk1opoYl2d4L0jkxcZBlksQkl+Np0D6RFEPmxz09zjYX6ZnUMdA2mRuH5m+1G+98qHfOqsar5xxeKoPteRl835C0u56+IFXLS4nBc+aEmrM+1begaZNcFSVpDFInzmnLlsPtA5tvtoJvr28/WM+gzP/emFXHJaOfc+s5Pf7jgW8eePnWY4zZ1ZQcmuFdEgosaMnWQ4xVJWkNOePk0Yg0tZ91y6EEj9ktZbjcf5q19/wPkLSvk/n1o5rbXua1dUcqx7kPeOdMdvgNMUrlo9nE+fXUOWRXhihvbTeuPDdl7Y2cKX1y1iYXkBD372bM6pdfK/nnyfV/a0RXSPxjjtzAqqLM5L6nKWBhE15qMiw+KIri/JT5+q9Q17XSyrLOKy0ysA2J3CJa39bX388c+3UVtq58HPnR3TKXWhrlw+C5vVwgsfpE933HDV6uGUF+Zw1fJZPL3t6IwrTB0aGeW+Z3dTW5rP3RcvACDPZuWR21dTV1XEl3+5nU37j095n4Z2NzarhTklsSXlx6ty5NLS40nazFWDiBrzUZFhcUTX+5swpr5OpNfjZeuhLtadXk5ZQQ6zi3LZdSw1QcTV5+ELP3mX3GwrP7njHBx50y/4KsrN5uLTylm/swWfL/VLWiOjPlx94avVw7llzVy6Bry8tDuyv8wzxcO/P8CB4/1864blJ+w+K8zN5qdfXMOCcjt3/WwrWw+OP9XiRI0uN7Vl+WRZ4/N2XFWcx9CIL2l/4GkQUWOCRYZ5tsi2Y6ZL/6xN+48z6jNcusQ/C6mrLmJXCpazBoZHuPOxrXT2D/Po7edQUxK/WpXrVlbS0uMZa9GfSsfdw/jMxNt7x1u7sIw5zjwe3zxzlrSOdA7ww9f3c/Xy2WM/d6GK8238/M5zqXTkcsdP3mXn0Yn/qGlwueO2lAWhJxwmJ7muQUQBHxUZRpoPAX/BYfegl9EU/3W8Ya+LotwsVs0pBmB5lYPGdjcDwyNJG8Ooz/DVx99jd3MP/37rKlZM0jImFpcvrcCWZeH5NFjSmqxaPZxggv3tpg6aZkiC/R+e34Mg/N31ExdSlhfm8Is/OpeivGw+/+hmPmw7uXp/aGSUw50D0253Emqs4DBJyXUNIgqIvMgwVKndhjHQlcIdWj6fYeOH7Vx8WvnYckBdtQNjoL4lOS03jDH8/XO7ebXexd/fsJzLl86K+2sU5mazbkl6LGm19kxeaBjOTasDCfZ3M79F/Ot723hlTxtfvXzxWJuRiVQV5/HLPzqXbKuFzz68mYPH+094/uDxAXyGaTdeDKUzEZUSkRYZhgpWrXelcElrT0sv7X1DrAtZUqirLgKSl1x/ZNMBfvb2Ie6+eAGfO782Ya9z7coqXH1DvDvFGnuiTdXyJJyKwlyuWJr5CXaPd5RvPbuHheX2iIsKa8vs/PKPzsU76uO2hzefMEOI9/Ze8P9xZ7NaaE7SDi0NIgqIvMgw1FjVegqDyIZAgeElSz6q9p1dlEup3ZaU5Pr/7GzhO+vr+fiK2dx79ekJfa3LT68gN9tyQpuUVGjtHSLbKjjzo+vzdcu5c+nsH+blDE6wP/i7Rg53DvCPN9ZFtetu8axCfn7nufQOernt4c24+vyBuLHdjUh8g4jFIsx25Cat9YkGkRlgT3MvV37vd2xu6oj5HtsPd0VUZBiqJA36Z23Y5+KMmhP7S4kIy6qK2HUsscn1bYe6+PqvdrBqTjHfu/lMLJbp9T2aij0ni8tOr2D9ztaU5qHaej1UFOZG/fVetKiMmpK8jD2D/VBHP/+xsZHrz6jigpDuApGqq3bwkzvOobXHw+cf2UL3wDANLjfVxXkRb2aJVDILDjWIzABPbzvKfpebP/rp1pj++u5wD3GwYyCqpSxI/Uyks3+Y9450h90dU1ft4MO2voQtnRw83s9dP9tKpSOXh28/J2kNBq9dUcVx9xBbDqRuSaulZzCiQsPxLBZ/i/i3Gjs4MC43kO6MMXzr2d1kW4S/mUb7mdW1Th76/Gqa2vu5/dEt7G7uiessJKg6iYdTaRDJcMYYXqlvZdXcYorysrn90S1R74B5bywfUhzV543NRFJUtf77/e0YA+tODxNEqhyM+AwftiZmN9A/rfe3uvjJHWvGckPJsO70cvKyrTz/QXPSXnO8tt6hKVueTOSms2uwWoQn3s2s2cgre9rYsK+db1x5WlS5oHAuXFzGf9x2Frube+Nyrno4lcW5tPZ6kjJj1SCS4fa19XGkc5CbV8/h53euAeBzj2yJqu3B9sNdZEVRZBiUbbVQlJtFZ4oKDjfsdVFqt7Gy+uTttMHkeiKaMY76DG83dfDxFbOZn+TOuvm2LC5bWsGLu1oZGfUl9bXB/0dLa0/khYbjVRTlcsXSCp7eepThkeSPPxaDw6P8/XN7WDKrkNsvqI3LPa9YNovv/+GZWARWhPn5na5KRx6jPkN7X+J/NzWIZLhXA/15Lj+9ggXlBfz0i2voGfTyuUe2RJyr2H64i6WVRTGty5YW5KRkOWvUZ/jdh+1cclp52LX5uc58CnOzErJDq76llz7PCOfOL437vSNx/cpKOvqH2ZyCJa3ewREGvaMxLWcF3XruPDr6h3n2/dTNpqLx7xv2c6x7kH/8RB3ZcaoqB7j+jCq2/M0V3HBGVdzuGRR6OFWiaRDJcK/saePMOcVUBP4yrKt28PDtqznSOcAXfrIF99DkBXcjoz7eP9IT9VJWUKqq1t8/2k3XgJdLwyxlgT+5vjxByfV3AhsYzl3gjPu9I3HpkgrybalZ0goWGkbSN2siFy8uY2llEf+xsSHlhapTaWp38+M3mvjUqmrWzI///++ygpyEbMhI5uFUGkQyWFuvh/eP9nDlshOL285bUMoDt/rXXO/+2VY83omTy/va+hj0jnLWvOiS6kGpCiIb97qwiP8NaSJ1VQ7qW3rjvuyz+UAn80rzx35Rky0328oVS2fx4q5WvEle0hqrVp/GTERE+PK6hTS19/PirtapPyFFjDHc9+xucrOtfDONznKJRNVYwaHORNQkgq2mxwcR8K+5/utNK3mrsYOvPv7ehG+kwSLDVXNiCyKlKQoiG/a1c9bcEoonqVWoq3YwNOKjsT1+O4F8PsOWA52cm4C/SqNx3cpKuga8vN0Y+7buWIxVq09jJgJwTV0lC8rt/PuGhrQ6JyXU/+xq5ff7j/PnVy2Z9tnnyVaUl0W+zZqUw6k0iGSwV+vbmFeaz+IJdnd8clUN37p+GS/vaeObz+wM+8saS5FhqBK7ja6B4aS+Ebj6POw81hN2V1ao5VWB5Hociw73tvbRM+jlvAWpyYcEXXxaOQU5WUlf0goeizud5SwAq0W455KF1Lf0jp0Fk076h0b4h+f2sKyyiNvOjfyUwnQhIkmrFdEgkqHcQyO81dDBlUtnTVog+IW18/n6FYt5attRvvNC/Ulv9rEUGYYqtdvwjhp6Pclrdvi7fe0AXLpk8jOpF5QXkJttiesOrY/yIakNIrnZVq5cNouXdrcldZdTa6/H31ZjmmekAHxiVTXVxXn88PX0m43c/9p+Wns9/OMn6uLWoj3ZqpJ0OFVmfncUb3zYzvCojyvCLGWN97XLF/OFC2p5eNMB/mNj49jjsRYZhnKmoGp94752KgpzWFZZNOl1VouwrLKI3XFMrm8+0MEcZx7VUzTeS4brVlbSM+jlzcapDz6Kl9aewWnPQoKyrRa+dOlC3jvcnfRlucnsb+vjkU0H+MPVczg7xlxhOqhy5NGchIJDDSIZ6tU9bRTnZ7M6gh9yEeHvrlvGJ1dV8y8v7eMX7xwCYi8yDPVREElOrYh31Mcb+9tZt6QiotlTXbWD3c09cel8+1E+JLWzkKALF5dRmJuV1BMPIz0WN1I3nV1DRWEO/76hIW73nA7vqI8/f/oD7DlZ/OXVS1I9nGmpLM7luHso4TNVDSIZaGTUx+v7XFx2ekXEU22LRfjup1dyxdIK/va3u3ju/eaYiwxDldr9CceOJFWtbz/URZ9nhHWnT76UFVRX5aB/eJRDnQPTfu0PXX10DXhTnlQPysmyctWy2by0uzVpnXHbej0xV6uHk5tt5a6LFvBWY0daHLj1vVc+5P0j3fyfT62gtCCzkunjVTnyMMb//yyRNIhkoHcPdtE94OXKKM+tyLZa+Pdbz+KcWiff+NUO/vu9YzEXGQY5CwLt4JN0psiGfe1kWYS1ETbAW14dv+T65iZ/cV+qk+qhrltZSZ9nJKKzvKfL4x2ls3942juzxrv13LkU52fzwOupnY281XCcB3/XyC1r5nDNisqUjiUeKpN0ONWMCCIislREHhSRp0XknlSPJ9FerW/DlmXh4tMi+2s8VG62lYdvX82S2YU093imtZQFjLUDT1bV+sZ9Ls6pdVKYG9nZ5YsrCrFZ45Ncf6epg+riPOY443fs7XStXVSGIy87KUtarl7/kuV0e0eNZ8/J4s6183ltrytpZ8CM19k/zNd/tYMFZXb+9rqJTyvMJMk6nCriICIiB0Vkp4jsEJGtYZ6fIyIbRKReRHaLyNdiHZSIPCoiLhHZFea5q0Vkn4g0iMi9AMaYemPMl4CbgdWxvm4mMMbwyp421i4sxZ6TFdM9inKz+ekX13DlslncuKp6WuPJs1nJy7YmpQljc/cge1v7Il7KArBlWVgyu3DayXVj0qM+ZDxbloWPLZ/Fy3vaJi0qjYdoj8WNxucvqKUwJ4v/2NA49cVxZozhL59+n+4BLz+85SzybbH9XqWbZLU+iXYmss4Yc6YxJtwb9QjwZ8aYpcB5wJdF5ISQLiIVIlI47rFFYe71GHD1+AdFxAo8AFwDLANuCb6GiNwAbAJei/Jryigftrk53DkQ0a6syZQV5PDQ51dPa2dWULKq1n/3oX9r77owrd8ns7yqiF3NPdPaRtrgctPRP5xWS1lB166swj00whuB70+itMRwLG6kHHnZfO78eazf1TJ22l+y/PydQ7xa7+Lea05nWdXkO/4ySb4tC0deduYsZxljWowx2wP/7gPqgfF/5l4C/FZEcgFE5C7g/jD3egMI111uDdBgjGkyxgwDTwA3Bj7nWWPMBcBt4cYnIteLyI97elIzXY6XV/b420RckYBzvGNVWmBLynLWhr0uqovzom6dvbzaQfeAl2PT+GVKdb+syVywsJSS/OyEn3jYFoeWJ5O588L55GRZ+NHG5M1G9rb28u0X6lm3pJw71tYm7XWTpao4L+H9s6IJIgZ4WUS2icjdk10oIrXAKmDzCTcw5ingReAJEbkN+CL+JahIVQNHQj4+ClSLyKUicr+I/CewPuzgjXnOGHO3wxH/tsvJ9Eq9izPmFMdtr348JGMmMjQyypsNx1l3ennUhZF1Y5XrsS9pvXOgk0pHLnPTKB8SlG21cHXdbF5N8JJWa88Q+TYrhTEuo06ltCCHW9fM4793HONIHHbTTWVweJQ//a/3KMrN5l9uOiPmgtt0VuXITXitSDRBZK0x5iz8S0lfFpGLw10kIgXAr4GvG2NO+q01xnwX8AA/Am4wxkQzdw33f9kYYzYaY75qjPljY8wDUdwvo7T1enj/SDdXLo1uOSfRkhFEth7son94NOqlLICllUVYLRJz0tYYw+Ymfz4kXd9orl1RRf/wKBsT2EKkrdd/jkgivwd3X7wAqwgP/i7xs5Fvv7CH/S4337v5jBOOV55JKotzE161HnEQMcY0B/7rAn6Df2npBCKSjT+A/NIY80y4+4jIRUBd4B73RTneo8CckI9rgMw4lCAOXq0PNlycneKRnKjUbqMjwcWGG/a6sGVZOH9h9DmJ3Gwri8oL2N0c20yksb2f4+6hlLc6mcx5C5yU2m08n8BdWi09gwlbygqa7cjlD86u4amtRxNa3/DirlZ+ufkwd1+8IKZdjpmi0pFH94CXweHEzVAjCiIiYg8mxEXEDlwF7Bp3jQCPAPXGmO9NcJ9VwEP48xh3AE4R+XYU430XWCwi80XEBnwGeDaKz89or+5pY64zn9Nmxf84zelw2nPweH0J/UHdsM/FeQtKY945s7y6KOZakc0H/PmQdEyqB2UFlrReq3cl7P9DW+9QQnZmjXfPJQsZNYaH3mhKyP1bega595kPWFHt4M+vyuyq9KkkY4dWpDORWcAmEXkf2AK8YIx5EUBE1otIFbAW+BxwWWAb8A4R+fi4++QDNxljGo0xPuB24ND4FxORx4G3gSUiclRE7gQwxowAXwFewp+4f9IYszvKrzkj9Q+N8GZjB1dM0XAxFZx2f81GomYjhzsGaGzvZ90UDRcnU1flwNU3hCuGv27faeqkojCH2tL0y4eEunZlJYPeUV7fG/8lLZ/PxL1afSJzS/O54Ywqfrn5cNyXSUd9hq8/sYPhER/337IqLo0k01kyDqeK6M86Y0wTcMYEzwUDRTPhcxah17457mMv/pnJ+OtumeQe65kgeT6TvfFhO8MjvrBnh6SaM9D6pLN/mJqS+L/RbvzQ/6YYSz4kqC5wjvXu5t6xUyAj4c+HdHDegtK0C97jnTu/lLKCHF7Y2cy1K+NbcX28f4gRn4lr36zJ/MmlC/nvHcf4yZsH+LM4zhZ+tLGBzQc6+ZdPr2R+mT1u901XwcOp0mEmomLw/17ex7+8tDcu93ql3t9w8Zza9OsqGmzCmKhtvhv2uphfZqd2Gr/0Syv95UnRLmkd7BjA1TeUllt7x7NahI+vmM3re130T3EscrTa4nSOSKQWzyrk6uWzeeytg/R6vHG557ZDXXz/1f1cf0YVnz67Ji73THezHDmIJLb1iQaRBDnSOcADGxp4YEPjtFtSjIz6eH2vi8uWRN5wMZlKg518E1C17vGO8lZjx5Rnh0ylMDeb+WX2qNufjNWHpEnn3qlcu6ISj9fHa3Fe0kpktfpEvrxuEX2eEX7+9kkr3lHr9Xj52hPvUenI5TufrEv7WWW85GRZKSvISehyVvq9I80Qj711EIsIp88u5K9/s5PWaezV3nrI33BxulXqiRJswpiIbb5vN3UwNOKb1lJW0PKqoqhrRTY3dVBWkMPC8sxY+lhd66SiMIcX4nziYfBY3GQtZ4F/CfLSJeU8sukAA8Oxz6yMMfzv3+yipcfDv31mFUUR9l2bKfy1IjoTySh9Hi+/evcI166s5IHbzmJoZJS/ePr9mM+0eGVPGzZrbA0Xk6EwJ4tsqyRkOWvjXhd52VbWxKFnVV21g2Pdg3RFOE5jDJsPdHLugvStDxnPv6RVyYZ97bjjuKTV2uvBapGkt0f/08sW0dk/zONbjkx98QR+vf0Yz77fzNcvX5zRh0zFqtKRl9AmjBpEEuCprUdxD41w54XzWVhewN9cu4zf7z/Oz94+GPW9jDG8Wt/GBYtKKUhQpfB0iQhOuy3iN+dIGWPYsK+dtYtKyc2OvV19UF2VP7m+pyWy2cjhzgFaejxpvbU3nOtWVjI84uPVPW1xu2drzxAVhTlYLckNpmfPc3LeAic/fqMxpjNTDhzv5+9+u4tz5zv5k3Xh2vTNfJXFubR0DybsCGINInE26jP85K0DrJ5XMnbY02fPncu6JeX88//sZX9bX1T32+9yc6hjIK16ZYVTkh///llNx/s53DnApXFYygL/chZEnlwfOz8kzTr3TuWsuSU47TbebIjfGSOtvfE7FjdaX1m3mLbeIZ7ednTCa0ZGfTS2u3lpdysPbGjgG7/awXU//D3X/NsbZFstfP8Pz0x6AEwXVY48+odH6fXEd7NFUHr+aZvBXq1v40jnIH99zdKxx0SE//vplXzs+2/wjSd38Mw9ayPen/7KnmCVenoHkdICW9yPyN0QSA5PN6keVGK3UV2cx64IK9ffaeqg1G6LuuFjqlkswopqBzvjcBBXUGuPh9NmFU59YQKsXVTKGXOKefB3jXzizGoOdw6w3+WmweWm0eVmv6uPA8f78Y5+9Jd2lSOXhRUF3LpmHp9cVU1VcV5Kxp4OgodTtfQM4siLfz5Ig0icPbLpADUleVy1/MTWJBWFufzzp1bypV9s499e+5C/+NjpEd3vlT1tnFHjSKuGi+E47Tns7OqO6z037mvntFkFca09qasuYnekM5EMy4eEWlHtYFPDcTze0bgsBbb1DnHR4tTk5ESEr6xbxF0/28ry+14ae9wiMNeZz6KKAi47fRaLKgpYXFHAwoqCtF36TYXQgsPTZ8e/1b1+p+No17Eethzo5H9fuzTs1PnqutncdHYNP9rYyLolFayunXyZxNXrYceRbv7sytMSNeS48ffPit9yVv/QCJsPdPDFtfPjdk+A5VUOXtrdRp/HO+npiEc6BzjWPcjdFy+I6+snS121g1Gfob6ll1XTPDOmz+PFPTSS8L5Zk7liaQVfv2IxPgOLKwpYVFHA/DJ7XALkTFcdmIVN5yiEyWhOJI4e2XQAu83KzefMmfCa+25YTnVJHt94cgd9UxRRvVrvX865cnl6L2WBv+CwzzPC8IgvLvd7u7ED76jhkjgtZQXVBc5cr2+ZPDeVzueHRGJFjX8TQTyWtIKNEJO5vXc8EeHrV5zG/7ryNK4/o4qllUUaQCJUXphDlkUS1s1Xg0ictPV6eP6DZm4+Z86k+9ALcrL4/s1ncqxrkH98fs+k93xlTytznHksSdFadDSCVetdA/GZjQR3UK2aE98tmcEdWlMl1zcf6KQkP5vTKtL/ex9OlSOXUruNnUenH0Rak1ytruLLahFmFeUmrOBQg0ic/PztQ4z4DF+4oHbKa1fXOrnn0oU8ufUoL+1uDXtNOjdcDGesaj1OS1qN7W6qi/PIs8X3r82KolzKC3OmrFx/p6mDNfOdWDJ0R4+IUBen5HoqqtVVfFUmsOBQg0gceLyj/HLzIa5cOot5pZFVNn/t8tOoqy7im8/sxNV38l8Iv9+fvg0XwylJQBBJ1K6ouqoi9kyyQ+tY9yBHuwYzrj5kvBXVDva73NM+7bA1gWerq+SoLE5cwaEGkTh4Zvsxuga83Hlh5ElgW5aFH/zhmfQPjfBXT39wUiHQy3vacORlc84Uyfd0URrHJow+n6HR1c/C8gQFkSneXDdnWL+siQST65EWV06ktddDcX625iAy2B9dOJ9//tSKhNxbg8g0GWN49M0DLK8qiro1x6KKQr55zels2NfOLzcfHnt8ZNTHhr0u1i0pJzsNGy6G4xxrwjj9WpGWXg+D3lEWViSmX9XyKv+b697W8Mn1d5o6cORlc/rszMyHBK2siSz/M5XWnuQcRqUS54w5xVywsCwh986Md6g09sb+4zS43Nx54fyYchefP7+WixaX8Z0X6mlq9x83v+1QF10D3rQ7Bncyxfk2ROKznNXo8n8fFiVoJjJV5frmA50ZnQ8JqoxTcr21N/HH4qrMpUFkmh7ZdICKwhyuW1kV0+dbLMK/3nQGtiwL3/jVDryjvrGGi/He3ppIVovErfVJYyCYLkxQTqSmJA9HXja7wyTXW3oGOdQxwLkZ1uoknHgl13UmoiajQWQa9rf18caH7Xz+/HnTOmZzVlEu//TJFbx/tIcfvt7AK/VtnLcwfRsuTsRpt8VlJtLgcuPIyx7Ls8Sb/801fFv4sX5ZGZ5UD5pucn14xEdH/5Bu71UT0iAyDY++eZCcLAu3njtv2ve6dmUln1pVzQ9f38+hjoGM2ZUVyhmnqvXGdjcLy+0J3dpcV+VgX2sf3tETiyM3H+igMDeLpZXxbw+RCitqppdcd/V5MCa1hYYqvWkQiVFn/zDPbD/Kp86qHksqT9e3blw+dibylWnetTccZ3582sE3tvcnvOnh8moHw6M+9re5T3j8naZO1tQ6Z0zH1xXV00uuB6vVZ2kQURPQIBKj/9p8iKERX1x7OxXlZvPQ51fznU/WZWQi01kw/eWsnkEv7X1DCdveG1QXTK6H5EVcvR4OHO+fMUtZMP3kerBaXXMiaiKZteieJoZHfPzs7UNctLiMxXFuSbKsqohlVZm5lFJqt9E1MIzPZ2Le2TSWVE9wEKkttWO3Wf0dfVf7e529c8CfD8nUflnhTDe53pKCY3FVZtGZSAxe2NmMq28oquLCU4HTbsNnoHtw8saSkxnb3pvg5SyLRVhe5TjhbJF3mjoozMli2QzJhwStrIk9ud7W6yEny5KQcyjUzKBBJErGGB7ZdIBFFQVckqZnnqfKWMHhNA6namzvx2a1UFOS+EOElgXan4z6/N0CNjd1sLq2hKwMKfCM1HQq11t7h5jtyM2I/m0qNWbWb0sSbDnQya5jvdyxtlZ/scYptecA0OGOPS/S4HJTW5aflDfyumoHg95RDhx34+rz0Njez7kzKB8SNJ3kemtP6o7FVZlBcyJRevTNAxTnZ/OpVTWpHkraccahCWNTu5slSWo3EjxbZNexXrKs/j8IZlJSPSiYXP8ghuR6a6+Hs6Z5qJWa2XQmEoXDHQO8vKeN286dG/cW5TNBaUEgiMR4psjwiI9DnQNJO9N8UXkBOVkWdh3rYXNTJ3abdWzX1kwiIqyocUQ9EzHG0Nar1epqcjoTicJP3jqAVYTPnVeb6qGkpeJ8f/K1M8blrEMd/Yz6TMJ3ZgVlWS2cXlnE7uZejruHWF3rnHH5kKAV1Q5+vz+6M9e7BrwMj/h0OUtNamb+xiRAn8fLU1uPct3Kyoys4UiGnCwrhTlZMVetJ2t7b6i6qiJ2HOlmv8s9o7b2jhdLcl2396pIzIggIiJLReRBEXlaRO5JxGv86t0juIdGuPPCBYm4/YwxnYLDxvZ+ABaUJ6YFfDjB5Dpk/vkhkwm2hY+m6FCr1VUk4hpEROSgiOwUkR0isnUa93lURFwisivMc1eLyD4RaRCRewGMMfXGmC8BNwOrY/8Kwhv1GR576yDn1JawIvDLqMKbThPGRpebKkcu9iQ2ngyeuZ6XbR17o52JZhflUlZgi6roUKvVVSQSMRNZZ4w50xhz0pu5iFSISOG4xxaFucdjwNVhPt8KPABcAywDbhGRZYHnbgA2Aa9N+ysYp8/j5ay5Jdx1kc5CplI6jSaMDe3uhLV/n8hpswvIsgira0sy5gCwWAQr16NJrrf2DGIRKC/MSeDIVKZL9m/NJcBvRSQXQETuAu4ff5Ex5g2gM8znrwEajDFNxphh4AngxsDnPGuMuQC4LdwLi8j1IvLjnp7otzkW59u4/5ZVXLU8cw6JShX/TCT6YkNjDI0ud1LzIeDP43zz40u559KFSX3dVAi2hR8cjqxyvbXXQ1lBzowOrmr64v3TYYCXRWSbiNx90pPGPAW8CDwhIrcBX8S/BBWpauBIyMdHgWoRuVRE7heR/wTWhx2YMc8ZY+52OGbukkU6cNpz6Or3nnRm/FTaeofoHx5N+kwE4M4L5yfs6NB0siLK5HqwWl2pycR78XmtMaZZRCqAV0Rkb2BWMcYY810ReQL4EbDQGOMOe6fwwpWIG2PMRmBjrINW8eO0ZzM86sM9NEJhbuT9lhpcwZ1ZyUuqn2pWhJy5fva8qQsIW3sGqS3V/x9qcnGdiRhjmgP/dQG/wb/8dAIRuQioCzx/X5QvcRSYE/JxDdAc02BVQjgDrU+iTa4Ht/cm6lx1FX1yvbXHozMRNaW4BRERsQeT5iJiB64Cdo27ZhXwEP48xh2AU0S+HcXLvAssFpH5ImIDPgM8G4/xq/gIHmkbbXK9sd1NYW6WJnETKJrk+sDwCL2eES00VFOK50xkFrBJRN4HtgAvGGNeHHdNPnCTMabRGOMDbgcOjb+RiDwOvA0sEZGjInIngDFmBPgK8BJQDzxpjNkdx69BTdNY/6woq9YbAkl1bWqZWCurHXzY1jdlcr21x18jooWGaipxy4kYY5qAM6a45s1xH3vxz0zGX3fLJPdYzwTJc5V6sTZhbGx3c+Eiba2faHXVDnwG9rT0TpoXaQ0UGmqNiJqK7t1TcRVswhjNclafx0tb7xALKzSJm2ihyfXJaLW6ipQGERVX+bYscrMtUdWKNAXanWhSPfEiTa639OhMREVGg4iKO2e+jc7+yI/IHdvem4IakVONiLCi2jFlD622Hg+FuVlJbUGjMpMGERV3/iaMkc9EGtvdZFmEuc78BI5KBfkr1ydPrrf2enQWoiKiQUTFndOeE1VivbHdTW2ZXdtrJElocn0iWiOiIqW/tSruom3C6N/eq0n1ZIkkua4zERUpDSIq7qJpB+8d9XGoYyDpjRdPZf7kes6EZ66PjPpo79O+WSoyGkRU3DntNgaGR/F4p+4We7hzgJEkHomrgsn1oglnIsfdw/gMWq2uIqJBRMVdNK1PGgM7sxbpzqykmiy5rsfiqmhoEFFxVxIIIl0RBJGGQOPFZB6JqyZPro8VGupMREVAg4iKu+hmIv3MKsqJqm28mr6VNcUA7DzafdJzwb5ZmhNRkdAgouLuo/5ZU9eKNLa7dSkrBWYV5VBWkMPOYyfPRFp6PdisFpz5thSMTGUaDSIq7koDZ4p0TNHJN1VH4qrJk+ttPR4qinKwWLSjspqaBhEVd0V5WWRZZMptvu19Q/QNjWgQSZGJkutaI6KioUFExZ2IUBJBrUgwqa5BJDVW1BQHkusnzka0Wl1FQ4OISohIqtZ1e29qraj2V66HNmM0xuhMREVFg4hKiJJ825RbfBvb+7HbrMwq0iNxUyFccr13cASP16czERUxDSIqIfydfKcKIm4WVuiRuKkSLrne0usvNNQgoiKlQUQlRKTLWXoQVWqtqClmv6uPgeERIKRGRJezVIQ0iKiEcNpt9Ax68Y76wj7fPzRCc49HD6JKsRWByvX6QOW6VquraGkQUQkRrFrvGgg/Gwkeiast4FNrfHI9eCyuBhEVKQ0iKiGcgYLDifIijbq9Ny3MKsqhvPCj5Hpbr4eyAhu2LH1rUJHRnxSVEGOtTyaoWm9wubFahHmlOhNJpbEz1491A/6ciM5CVDQ0iKiEcE7RhLGx3c08Z77+xZsG6qodNLjcDAyP0No7pEl1FRX9DVYJ4ZwiJ9LY7maBLmWlhdDkemvPoG7vVVHRIKISoiTf39o9XBPGkVEfB48PaKV6mlgZOHN968Euuga8OhNRUdEgohIiy2qhOD87bGL9SNcgw6M+3ZmVJmYV5VJemMOr9W3+j3UmoqKgQUQljHOCJozBnllaI5I+VlQ72HaoC9BjcVV0NIiohPFXrZ98MJVu700/weNyQavVVXQ0iKiEmWgm0uByU16YgyNPj8RNFysDRYegy1kqOhpEVMJMuJzV7tZ8SJpZEUiu221WCnOyUjwalUkyPoiIyFIReVBEnhaRe1I9HvURp91G14AXX3CdhMCRuO39upSVZoLJ9VmOXO2qrKIScRAREauIvCciz0/w/DdEZLeI7BKRx0UkpjmxiDwqIi4R2RXmuatFZJ+INIjIvQDGmHpjzJeAm4HVsbymSgynPYdRn6HX4x17rKN/mJ5Br27vTUPXrazkokVlqR6GyjDRzES+BtSHe0JEqoGvAquNMXWAFfjMuGsqRKRw3GOLwtzuMeDqMK9hBR4ArgGWAbeIyLLAczcAm4DXovh6VIKVhqlab3BpUj1d3Xf9cv7+xrpUD0NlmIiCiIjUANcCD09yWRaQJyJZQD7QPO75S4DfBmcoInIXcP/4mxhj3gA6w9x/DdBgjGkyxgwDTwA3Bj7nWWPMBcBtk3wN14vIj3t6eia6RMXZWP+skCAytjNLZyJKzQiRzkR+APwlEPZwCGPMMeBfgcNAC9BjjHl53DVPAS8CT4jIbcAX8S9BRaoaOBLy8VGgWkQuFZH7ReQ/gfUTfbIx5jljzN0Oh2OiS1ScjfXPCqlab3T1k2+zUqnbSJWaEaYMIiJyHeAyxmyb5JoS/LOC+UAVYBeRz46/zhjzXcAD/Ai4wRjjjmKs4bJ9xhiz0RjzVWPMHxtjHojifirBSgtOnok0tLtZUG7HYtHkrVIzQSQzkbXADSJyEP8S0mUi8otx11wBHDDGtBtjvMAzwAXjbyQiFwF1wG+A+6Ic61FgTsjHNZy8ZKbSSEl+MIh8VHDY6HJrPkSpGWTKIGKM+aYxpsYYU4s/Wf66MWb8LOMwcJ6I5It/f+DljEvCi8gq4CH8M5Y7AKeIfDuKsb4LLBaR+SJiC4zl2Sg+XyVZbrYVu81KZ79/d9bg8CjHugc1iCg1g0yrTkRE1otIlTFmM/A0sB3YGbjvj8ddng/cZIxpNMb4gNuBQ2Hu+TjwNrBERI6KyJ0AxpgR4CvAS/gD1JPGmN3TGb9KPGeBbWwmEkyq6/ZepWaOqEpTjTEbgY0hH3885N/3MckSlTHmzXEfe/HPTMZfd8sk91jPJMlzlX6c9pyxLb7aM0upmSfjK9ZVeisNaX3S2N6PRaC2LD/Fo1JKxYsGEZVQzhOCiJu5znxysqwpHpVSKl40iKiE8reDH/b3zNKdWUrNOBpEVEI57TaGR3z0DY3QdLxfK9WVmmE0iKiEKglUrX9wpIfhET0SV6mZRoOISqhgE8YtB/3t0HR7r1IziwYRlVDB/lnvHvAHkQVlGkSUmkk0iKiEKrXnAPDekS5K7bax5S2l1MygQUQllDPQhNHj9WlSXakZSIOISii7zYoty/9jptt7lZp5NIiohBKRseS67sxSaubRIKISLtgSXpezlJp5NIiohAseTrVIl7OUmnE0iKiEc9pt5GRZqC7OS/VQlFJxFlUreKVi8dnz5nFOrVOPxFVqBtIgohLunFon59Q6Uz0MpVQC6HKWUkqpmGkQUUopFTMNIkoppWKmQUQppVTMNIgopZSKmQYRpZRSMdMgopRSKmYaRJRSSsVMjDGpHkNSiUg7cCjGTy8DjsdxOJlKvw9++n3w0++D30z+PswzxpSHe+KUCyLTISJbjTGrUz2OVNPvg59+H/z0++B3qn4fdDlLKaVUzDSIKKWUipkGkej8ONUDSBP6ffDT74Offh/8Tsnvg+ZElFJKxUxnIkoppWKmQUQppVTMNIhEQESuFpF9ItIgIvemejypJCIHRWSniOwQka2pHk+yiMijIuISkV0hjzlF5BUR2R/4b0kqx5gME3wfviUixwI/EztE5OOpHGMyiMgcEdkgIvUisltEvhZ4/JT7mdAgMgURsQIPANcAy4BbRGRZakeVcuuMMWeeYnviHwOuHvfYvcBrxpjFwGuBj2e6xzj5+wDw/cDPxJnGmPVJHlMqjAB/ZoxZCpwHfDnwvnDK/UxoEJnaGqDBGNNkjBkGngBuTPGYVJIZY94AOsc9fCPw08C/fwp8IpljSoUJvg+nHGNMizFme+DffUA9UM0p+DOhQWRq1cCRkI+PBh47VRngZRHZJiJ3p3owKTbLGNMC/jcVoCLF40mlr4jIB4Hlrhm/hBNKRGqBVcBmTsGfCQ0iU5Mwj53K+6LXGmPOwr+892URuTjVA1Ip9yNgIXAm0AL8v5SOJolEpAD4NfB1Y0xvqseTChpEpnYUmBPycQ3QnKKxpJwxpjnwXxfwG/zLfaeqNhGpBAj815Xi8aSEMabNGDNqjPEBD3GK/EyISDb+APJLY8wzgYdPuZ8JDSJTexdYLCLzRcQGfAZ4NsVjSgkRsYtIYfDfwFXArsk/a0Z7Frg98O/bgd+mcCwpE3zTDPgkp8DPhIgI8AhQb4z5XshTp9zPhFasRyCwZfEHgBV41BjzndSOKDVEZAH+2QdAFvBfp8r3QkQeBy7F3+67DbgP+G/gSWAucBi4yRgzo5POE3wfLsW/lGWAg8AfB/MCM5WIXAj8HtgJ+AIP/zX+vMip9TOhQUQppVSsdDlLKaVUzDSIKKWUipkGEaWUUjHTIKKUUipmGkSUUkrFTIOIUgkkIrWhHW+Vmmk0iCiVYUQkK9VjUCpIg4hSiWcVkYcC5068LCJ5InKmiLwTaFr4m2DTQhHZKCKrA/8uE5GDgX9/QUSeEpHngJdT96UodSINIkol3mLgAWPMcqAb+APgZ8BfGWNW4q96vi+C+5wP3G6MuSxRA1UqWhpElEq8A8aYHYF/b8Pf8bbYGPO7wGM/BSLphvzKTG+hoTKPBhGlEm8o5N+jQPEk147w0e9l7rjn+uM4JqXiQoOIUsnXA3SJyEWBjz8HBGclB4GzA//+dJLHpVTUdJeHUqlxO/CgiOQDTcAdgcf/FXhSRD4HvJ6qwSkVKe3iq5RSKma6nKWUUipmGkSUUkrFTIOIUkqpmGkQUUopFTMNIkoppWKmQUQppVTMNIgopZSK2f8HuCjxlMFyNtAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(['hour'])['event_uuid'].count().plot(logy=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a0b6eba",
   "metadata": {},
   "source": [
    "# Transformation of Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "10d17a32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day  user_neighborhood\n",
       "5    Manhattan             6869\n",
       "     Brooklyn              2009\n",
       "     Queens                 595\n",
       "     Bronx                  250\n",
       "     Staten Island          168\n",
       "6    Manhattan            12591\n",
       "     Brooklyn              3737\n",
       "     Queens                 842\n",
       "     Bronx                  533\n",
       "     Staten Island          353\n",
       "7    Manhattan            12807\n",
       "     Brooklyn              3590\n",
       "     Queens                 905\n",
       "     Bronx                  507\n",
       "     Staten Island          393\n",
       "8    Manhattan            12180\n",
       "     Brooklyn              4025\n",
       "     Queens                 893\n",
       "     Bronx                  469\n",
       "     Staten Island          396\n",
       "9    Manhattan            12270\n",
       "     Brooklyn              3440\n",
       "     Queens                1026\n",
       "     Bronx                  510\n",
       "     Staten Island          354\n",
       "10   Manhattan            12371\n",
       "     Brooklyn              3400\n",
       "     Queens                1069\n",
       "     Staten Island          460\n",
       "     Bronx                  394\n",
       "11   Manhattan            12201\n",
       "     Brooklyn              3556\n",
       "     Queens                 936\n",
       "     Bronx                  558\n",
       "     Staten Island          344\n",
       "12   Manhattan             5580\n",
       "     Brooklyn              1594\n",
       "     Queens                 386\n",
       "     Bronx                  231\n",
       "     Staten Island          188\n",
       "Name: user_neighborhood, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['day'])['user_neighborhood'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a53ed101",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day  event_page \n",
       "5    search_page    3995\n",
       "     splash_page    2954\n",
       "     book_page      1977\n",
       "     driver_page     965\n",
       "6    search_page    7219\n",
       "     splash_page    5466\n",
       "     book_page      3548\n",
       "     driver_page    1823\n",
       "7    search_page    7307\n",
       "     splash_page    5448\n",
       "     book_page      3576\n",
       "     driver_page    1871\n",
       "8    search_page    7221\n",
       "     splash_page    5376\n",
       "     book_page      3572\n",
       "     driver_page    1794\n",
       "9    search_page    6979\n",
       "     splash_page    5280\n",
       "     book_page      3586\n",
       "     driver_page    1755\n",
       "10   search_page    7201\n",
       "     splash_page    5380\n",
       "     book_page      3424\n",
       "     driver_page    1689\n",
       "11   search_page    7137\n",
       "     splash_page    5184\n",
       "     book_page      3506\n",
       "     driver_page    1768\n",
       "12   search_page    3174\n",
       "     splash_page    2365\n",
       "     book_page      1639\n",
       "     driver_page     801\n",
       "Name: event_page, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " df.groupby(['day'])['event_page'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "407f71bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>event_page</th>\n",
       "      <th>book_page</th>\n",
       "      <th>driver_page</th>\n",
       "      <th>search_page</th>\n",
       "      <th>splash_page</th>\n",
       "      <th>booking to search ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1977</td>\n",
       "      <td>965</td>\n",
       "      <td>3995</td>\n",
       "      <td>2954</td>\n",
       "      <td>49.486859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3548</td>\n",
       "      <td>1823</td>\n",
       "      <td>7219</td>\n",
       "      <td>5466</td>\n",
       "      <td>49.148081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3576</td>\n",
       "      <td>1871</td>\n",
       "      <td>7307</td>\n",
       "      <td>5448</td>\n",
       "      <td>48.939373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3572</td>\n",
       "      <td>1794</td>\n",
       "      <td>7221</td>\n",
       "      <td>5376</td>\n",
       "      <td>49.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3586</td>\n",
       "      <td>1755</td>\n",
       "      <td>6979</td>\n",
       "      <td>5280</td>\n",
       "      <td>51.382720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3424</td>\n",
       "      <td>1689</td>\n",
       "      <td>7201</td>\n",
       "      <td>5380</td>\n",
       "      <td>47.548952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3506</td>\n",
       "      <td>1768</td>\n",
       "      <td>7137</td>\n",
       "      <td>5184</td>\n",
       "      <td>49.124282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1639</td>\n",
       "      <td>801</td>\n",
       "      <td>3174</td>\n",
       "      <td>2365</td>\n",
       "      <td>51.638311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "event_page  book_page  driver_page  search_page  splash_page  \\\n",
       "day                                                            \n",
       "5                1977          965         3995         2954   \n",
       "6                3548         1823         7219         5466   \n",
       "7                3576         1871         7307         5448   \n",
       "8                3572         1794         7221         5376   \n",
       "9                3586         1755         6979         5280   \n",
       "10               3424         1689         7201         5380   \n",
       "11               3506         1768         7137         5184   \n",
       "12               1639          801         3174         2365   \n",
       "\n",
       "event_page  booking to search ratio  \n",
       "day                                  \n",
       "5                         49.486859  \n",
       "6                         49.148081  \n",
       "7                         48.939373  \n",
       "8                         49.466833  \n",
       "9                         51.382720  \n",
       "10                        47.548952  \n",
       "11                        49.124282  \n",
       "12                        51.638311  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = df.groupby(['event_page'])['day'].value_counts().unstack().T\n",
    "t\n",
    "t['booking to search ratio'] = t['book_page']/t['search_page']*100\n",
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7622bf37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day  device_type\n",
       "5    mobile_web     5149\n",
       "     ios            2384\n",
       "     android        1463\n",
       "     desktop_web     895\n",
       "6    mobile_web     8842\n",
       "     ios            4337\n",
       "     android        2870\n",
       "     desktop_web    2007\n",
       "7    mobile_web     9531\n",
       "     ios            4217\n",
       "     android        2854\n",
       "     desktop_web    1600\n",
       "8    mobile_web     8903\n",
       "     ios            4373\n",
       "     android        2729\n",
       "     desktop_web    1958\n",
       "9    mobile_web     8764\n",
       "     ios            4380\n",
       "     android        2744\n",
       "     desktop_web    1712\n",
       "10   mobile_web     8784\n",
       "     ios            4482\n",
       "     android        2562\n",
       "     desktop_web    1866\n",
       "11   mobile_web     8646\n",
       "     ios            4500\n",
       "     android        2672\n",
       "     desktop_web    1777\n",
       "12   mobile_web     4040\n",
       "     ios            2026\n",
       "     android        1231\n",
       "     desktop_web     682\n",
       "Name: device_type, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['day'])['device_type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "e1649c88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>device_type</th>\n",
       "      <th>android</th>\n",
       "      <th>desktop_web</th>\n",
       "      <th>ios</th>\n",
       "      <th>mobile_web</th>\n",
       "      <th>web to mobile ratio</th>\n",
       "      <th>mobile web to tot.mobile</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1463</td>\n",
       "      <td>895</td>\n",
       "      <td>2384</td>\n",
       "      <td>5149</td>\n",
       "      <td>1.571094</td>\n",
       "      <td>1.338446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2870</td>\n",
       "      <td>2007</td>\n",
       "      <td>4337</td>\n",
       "      <td>8842</td>\n",
       "      <td>1.505342</td>\n",
       "      <td>1.226863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2854</td>\n",
       "      <td>1600</td>\n",
       "      <td>4217</td>\n",
       "      <td>9531</td>\n",
       "      <td>1.574176</td>\n",
       "      <td>1.347900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2729</td>\n",
       "      <td>1958</td>\n",
       "      <td>4373</td>\n",
       "      <td>8903</td>\n",
       "      <td>1.529288</td>\n",
       "      <td>1.253591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2744</td>\n",
       "      <td>1712</td>\n",
       "      <td>4380</td>\n",
       "      <td>8764</td>\n",
       "      <td>1.470522</td>\n",
       "      <td>1.230208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2562</td>\n",
       "      <td>1866</td>\n",
       "      <td>4482</td>\n",
       "      <td>8784</td>\n",
       "      <td>1.511925</td>\n",
       "      <td>1.247019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2672</td>\n",
       "      <td>1777</td>\n",
       "      <td>4500</td>\n",
       "      <td>8646</td>\n",
       "      <td>1.453291</td>\n",
       "      <td>1.205521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1231</td>\n",
       "      <td>682</td>\n",
       "      <td>2026</td>\n",
       "      <td>4040</td>\n",
       "      <td>1.449800</td>\n",
       "      <td>1.240405</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "device_type  android  desktop_web   ios  mobile_web  web to mobile ratio  \\\n",
       "day                                                                        \n",
       "5               1463          895  2384        5149             1.571094   \n",
       "6               2870         2007  4337        8842             1.505342   \n",
       "7               2854         1600  4217        9531             1.574176   \n",
       "8               2729         1958  4373        8903             1.529288   \n",
       "9               2744         1712  4380        8764             1.470522   \n",
       "10              2562         1866  4482        8784             1.511925   \n",
       "11              2672         1777  4500        8646             1.453291   \n",
       "12              1231          682  2026        4040             1.449800   \n",
       "\n",
       "device_type  mobile web to tot.mobile  \n",
       "day                                    \n",
       "5                            1.338446  \n",
       "6                            1.226863  \n",
       "7                            1.347900  \n",
       "8                            1.253591  \n",
       "9                            1.230208  \n",
       "10                           1.247019  \n",
       "11                           1.205521  \n",
       "12                           1.240405  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t2 = df.groupby(['day'])['device_type'].value_counts().unstack()\n",
    "t2\n",
    "t2['web to mobile ratio'] = (t2['mobile_web']+t2['desktop_web'])/(t2['ios']+t2['android'])\n",
    "t2['mobile web to tot.mobile'] = (t2['mobile_web'])/(t2['ios']+t2['android'])\n",
    "t2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6ead5388",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "day  event_type \n",
       "5    open            6594\n",
       "     choose_car      1498\n",
       "     search          1484\n",
       "     request_car      277\n",
       "     begin_ride        38\n",
       "6    open           11733\n",
       "     search          2891\n",
       "     choose_car      2843\n",
       "     request_car      540\n",
       "     begin_ride        49\n",
       "7    open           11767\n",
       "     choose_car      2953\n",
       "     search          2824\n",
       "     request_car      596\n",
       "     begin_ride        62\n",
       "8    open           11662\n",
       "     search          2899\n",
       "     choose_car      2769\n",
       "     request_car      547\n",
       "     begin_ride        86\n",
       "9    open           11531\n",
       "     search          2749\n",
       "     choose_car      2725\n",
       "     request_car      538\n",
       "     begin_ride        57\n",
       "10   open           11325\n",
       "     search          2904\n",
       "     choose_car      2801\n",
       "     request_car      607\n",
       "     begin_ride        57\n",
       "11   open           11371\n",
       "     search          2821\n",
       "     choose_car      2804\n",
       "     request_car      521\n",
       "     begin_ride        78\n",
       "12   open            5133\n",
       "     search          1307\n",
       "     choose_car      1301\n",
       "     request_car      220\n",
       "     begin_ride        18\n",
       "Name: event_type, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['day'])['event_type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9415fd94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>day</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>begin_ride</th>\n",
       "      <td>38</td>\n",
       "      <td>49</td>\n",
       "      <td>62</td>\n",
       "      <td>86</td>\n",
       "      <td>57</td>\n",
       "      <td>57</td>\n",
       "      <td>78</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>choose_car</th>\n",
       "      <td>1498</td>\n",
       "      <td>2843</td>\n",
       "      <td>2953</td>\n",
       "      <td>2769</td>\n",
       "      <td>2725</td>\n",
       "      <td>2801</td>\n",
       "      <td>2804</td>\n",
       "      <td>1301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open</th>\n",
       "      <td>6594</td>\n",
       "      <td>11733</td>\n",
       "      <td>11767</td>\n",
       "      <td>11662</td>\n",
       "      <td>11531</td>\n",
       "      <td>11325</td>\n",
       "      <td>11371</td>\n",
       "      <td>5133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>request_car</th>\n",
       "      <td>277</td>\n",
       "      <td>540</td>\n",
       "      <td>596</td>\n",
       "      <td>547</td>\n",
       "      <td>538</td>\n",
       "      <td>607</td>\n",
       "      <td>521</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>search</th>\n",
       "      <td>1484</td>\n",
       "      <td>2891</td>\n",
       "      <td>2824</td>\n",
       "      <td>2899</td>\n",
       "      <td>2749</td>\n",
       "      <td>2904</td>\n",
       "      <td>2821</td>\n",
       "      <td>1307</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "day            5      6      7      8      9      10     11    12\n",
       "event_type                                                       \n",
       "begin_ride     38     49     62     86     57     57     78    18\n",
       "choose_car   1498   2843   2953   2769   2725   2801   2804  1301\n",
       "open         6594  11733  11767  11662  11531  11325  11371  5133\n",
       "request_car   277    540    596    547    538    607    521   220\n",
       "search       1484   2891   2824   2899   2749   2904   2821  1307"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['event_type'])['day'].value_counts().unstack()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b11c8b3",
   "metadata": {},
   "source": [
    "## Rolling means and variances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "838a874f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa5b1068550>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Rolling Mean & Std of Events visualised for the week', size=16, y=0.95, weight='bold')\n",
    "\n",
    "# sns.countplot(x='dates', data=df, ax=ax)\n",
    "\n",
    "df['day'].value_counts().sort_index().plot(grid=True, label='Original')\n",
    "df['rolmean_day'] =  df['day'].rolling(window=3).mean()\n",
    "df['rolmean_day'].value_counts().sort_index().plot(color='blue', label='Rolling Mean')\n",
    "df['rolstd_day'] =  df['day'].rolling(window=3).std()\n",
    "df['rolstd_day'].value_counts().sort_index().plot(color='red', label='Rolling Std')\n",
    "\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('Count of Events for the day ', fontsize=16)\n",
    "plt.legend(loc='best')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ee502141",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count of Events for the day ')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1, figsize=(16,8))\n",
    "fig.suptitle('Rolling Mean & Std Deviation of Events visualised for the week', size=16, y=0.95, weight='bold')\n",
    "\n",
    "df['hour'] =  df['event_time'].dt.hour\n",
    "df['rolmean_h'] =  df['hour'].rolling(window=3).mean()\n",
    "df['rolstd_h'] =  df['hour'].rolling(window=3).std()\n",
    "\n",
    "df['hour'].value_counts().sort_index().plot(grid=True, color='black')\n",
    "df['rolmean_h'].value_counts().sort_index().plot(color='blue')\n",
    "df['rolstd_h'].value_counts().sort_index().plot(color='red')\n",
    "\n",
    "ax.set_xlabel('HOUR', fontsize=16)\n",
    "ax.set_ylabel('Count of Events for the day ', fontsize=16)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "62653602",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # logscale \n",
    "\n",
    "# fig,ax = plt.subplots(1, figsize=(16,8))\n",
    "# fig.suptitle('Rolling Mean & Std Deviation of Events visualised for the week', size=16, y=0.95, weight='bold')\n",
    "\n",
    "# df_log= np.log(df['day'])\n",
    "# plt.plot(df_log)\n",
    "\n",
    "# ax.set_xlabel('HOUR', fontsize=16)\n",
    "# ax.set_ylabel('Count of Events for the day ', fontsize=16)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ae3c5ef",
   "metadata": {},
   "source": [
    "## Logarithms \n",
    "\n",
    "To understand changes over time that are either too small or too large we switch to logarithms \n",
    "\n",
    "Let us explore the changes happening across `event_page` and `event_type` and `device_type` which as per the above visualisations showcase only 'small' changes happening across time.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c0d47277",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 124980 entries, 0 to 124979\n",
      "Data columns (total 16 columns):\n",
      " #   Column             Non-Null Count   Dtype         \n",
      "---  ------             --------------   -----         \n",
      " 0   Unnamed: 0         124980 non-null  int64         \n",
      " 1   event_uuid         124980 non-null  object        \n",
      " 2   user_uuid          124980 non-null  object        \n",
      " 3   event_time         124980 non-null  datetime64[ns]\n",
      " 4   device_type        124980 non-null  object        \n",
      " 5   session_uuid       124980 non-null  object        \n",
      " 6   user_neighborhood  124980 non-null  object        \n",
      " 7   event_page         124980 non-null  object        \n",
      " 8   event_type         124980 non-null  object        \n",
      " 9   month              124980 non-null  int64         \n",
      " 10  day                124980 non-null  int64         \n",
      " 11  hour               124980 non-null  int64         \n",
      " 12  rolmean_day        124978 non-null  float64       \n",
      " 13  rolstd_day         124978 non-null  float64       \n",
      " 14  rolmean_h          124978 non-null  float64       \n",
      " 15  rolstd_h           124978 non-null  float64       \n",
      "dtypes: datetime64[ns](1), float64(4), int64(4), object(7)\n",
      "memory usage: 15.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c24c391b",
   "metadata": {},
   "source": [
    "## Event_Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "3120fe60",
   "metadata": {},
   "outputs": [],
   "source": [
    "event_type = df.groupby(['event_type'])['day'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "b68ebeee",
   "metadata": {},
   "outputs": [],
   "source": [
    "event_type_1 = event_type.unstack(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "8477aa54",
   "metadata": {},
   "outputs": [],
   "source": [
    "event_type_1['begin_ride to request_car'] = event_type_1['begin_ride']/event_type_1['request_car']*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "dc1d3a3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>event_type</th>\n",
       "      <th>begin_ride</th>\n",
       "      <th>choose_car</th>\n",
       "      <th>open</th>\n",
       "      <th>request_car</th>\n",
       "      <th>search</th>\n",
       "      <th>begin_ride to request_car</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>38</td>\n",
       "      <td>1498</td>\n",
       "      <td>6594</td>\n",
       "      <td>277</td>\n",
       "      <td>1484</td>\n",
       "      <td>13.718412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>49</td>\n",
       "      <td>2843</td>\n",
       "      <td>11733</td>\n",
       "      <td>540</td>\n",
       "      <td>2891</td>\n",
       "      <td>9.074074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>62</td>\n",
       "      <td>2953</td>\n",
       "      <td>11767</td>\n",
       "      <td>596</td>\n",
       "      <td>2824</td>\n",
       "      <td>10.402685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>86</td>\n",
       "      <td>2769</td>\n",
       "      <td>11662</td>\n",
       "      <td>547</td>\n",
       "      <td>2899</td>\n",
       "      <td>15.722121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>57</td>\n",
       "      <td>2725</td>\n",
       "      <td>11531</td>\n",
       "      <td>538</td>\n",
       "      <td>2749</td>\n",
       "      <td>10.594796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>57</td>\n",
       "      <td>2801</td>\n",
       "      <td>11325</td>\n",
       "      <td>607</td>\n",
       "      <td>2904</td>\n",
       "      <td>9.390445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>78</td>\n",
       "      <td>2804</td>\n",
       "      <td>11371</td>\n",
       "      <td>521</td>\n",
       "      <td>2821</td>\n",
       "      <td>14.971209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>18</td>\n",
       "      <td>1301</td>\n",
       "      <td>5133</td>\n",
       "      <td>220</td>\n",
       "      <td>1307</td>\n",
       "      <td>8.181818</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "event_type  begin_ride  choose_car   open  request_car  search  \\\n",
       "day                                                              \n",
       "5                   38        1498   6594          277    1484   \n",
       "6                   49        2843  11733          540    2891   \n",
       "7                   62        2953  11767          596    2824   \n",
       "8                   86        2769  11662          547    2899   \n",
       "9                   57        2725  11531          538    2749   \n",
       "10                  57        2801  11325          607    2904   \n",
       "11                  78        2804  11371          521    2821   \n",
       "12                  18        1301   5133          220    1307   \n",
       "\n",
       "event_type  begin_ride to request_car  \n",
       "day                                    \n",
       "5                           13.718412  \n",
       "6                            9.074074  \n",
       "7                           10.402685  \n",
       "8                           15.722121  \n",
       "9                           10.594796  \n",
       "10                           9.390445  \n",
       "11                          14.971209  \n",
       "12                           8.181818  "
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "event_type_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "79219a07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event_type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>begin_ride</th>\n",
       "      <td>8.0</td>\n",
       "      <td>55.625000</td>\n",
       "      <td>21.507059</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>46.250000</td>\n",
       "      <td>57.00000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>86.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>choose_car</th>\n",
       "      <td>8.0</td>\n",
       "      <td>2461.750000</td>\n",
       "      <td>661.033984</td>\n",
       "      <td>1301.000000</td>\n",
       "      <td>2418.250000</td>\n",
       "      <td>2785.00000</td>\n",
       "      <td>2813.750000</td>\n",
       "      <td>2953.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open</th>\n",
       "      <td>8.0</td>\n",
       "      <td>10139.500000</td>\n",
       "      <td>2672.609533</td>\n",
       "      <td>5133.000000</td>\n",
       "      <td>10142.250000</td>\n",
       "      <td>11451.00000</td>\n",
       "      <td>11679.750000</td>\n",
       "      <td>11767.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>request_car</th>\n",
       "      <td>8.0</td>\n",
       "      <td>480.750000</td>\n",
       "      <td>147.126525</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>460.000000</td>\n",
       "      <td>539.00000</td>\n",
       "      <td>559.250000</td>\n",
       "      <td>607.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>search</th>\n",
       "      <td>8.0</td>\n",
       "      <td>2484.875000</td>\n",
       "      <td>676.016787</td>\n",
       "      <td>1307.000000</td>\n",
       "      <td>2432.750000</td>\n",
       "      <td>2822.50000</td>\n",
       "      <td>2893.000000</td>\n",
       "      <td>2904.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>begin_ride to request_car</th>\n",
       "      <td>8.0</td>\n",
       "      <td>11.506945</td>\n",
       "      <td>2.882601</td>\n",
       "      <td>8.181818</td>\n",
       "      <td>9.311352</td>\n",
       "      <td>10.49874</td>\n",
       "      <td>14.031611</td>\n",
       "      <td>15.722121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           count          mean          std          min  \\\n",
       "event_type                                                                 \n",
       "begin_ride                   8.0     55.625000    21.507059    18.000000   \n",
       "choose_car                   8.0   2461.750000   661.033984  1301.000000   \n",
       "open                         8.0  10139.500000  2672.609533  5133.000000   \n",
       "request_car                  8.0    480.750000   147.126525   220.000000   \n",
       "search                       8.0   2484.875000   676.016787  1307.000000   \n",
       "begin_ride to request_car    8.0     11.506945     2.882601     8.181818   \n",
       "\n",
       "                                    25%          50%           75%  \\\n",
       "event_type                                                           \n",
       "begin_ride                    46.250000     57.00000     66.000000   \n",
       "choose_car                  2418.250000   2785.00000   2813.750000   \n",
       "open                       10142.250000  11451.00000  11679.750000   \n",
       "request_car                  460.000000    539.00000    559.250000   \n",
       "search                      2432.750000   2822.50000   2893.000000   \n",
       "begin_ride to request_car      9.311352     10.49874     14.031611   \n",
       "\n",
       "                                    max  \n",
       "event_type                               \n",
       "begin_ride                    86.000000  \n",
       "choose_car                  2953.000000  \n",
       "open                       11767.000000  \n",
       "request_car                  607.000000  \n",
       "search                      2904.000000  \n",
       "begin_ride to request_car     15.722121  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "event_type_1.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "511abd16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'COUNT ')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Events_type by total count per day', size=16, y=0.95, weight='bold')\n",
    "\n",
    "event_type_1.plot(ax=ax, grid=True)\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('COUNT ', fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "952f4539",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8584bf7f10>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Day wise movement on Events_Type category', size=16, y=0.95, weight='bold')\n",
    "\n",
    "event_type_1.plot(ax=ax, legend=True, grid=True, logy=True)\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('Log (COUNT) ', fontsize=16)\n",
    "plt.legend(loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4bfe0294",
   "metadata": {},
   "source": [
    "## Device_Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "88a3ec60",
   "metadata": {},
   "outputs": [],
   "source": [
    "device_type = df.groupby(['device_type'])['day'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ac2c3e9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "device_type_1 = device_type.unstack(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "cea59ba0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>device_type</th>\n",
       "      <th>android</th>\n",
       "      <th>desktop_web</th>\n",
       "      <th>ios</th>\n",
       "      <th>mobile_web</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1463</td>\n",
       "      <td>895</td>\n",
       "      <td>2384</td>\n",
       "      <td>5149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2870</td>\n",
       "      <td>2007</td>\n",
       "      <td>4337</td>\n",
       "      <td>8842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2854</td>\n",
       "      <td>1600</td>\n",
       "      <td>4217</td>\n",
       "      <td>9531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2729</td>\n",
       "      <td>1958</td>\n",
       "      <td>4373</td>\n",
       "      <td>8903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2744</td>\n",
       "      <td>1712</td>\n",
       "      <td>4380</td>\n",
       "      <td>8764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2562</td>\n",
       "      <td>1866</td>\n",
       "      <td>4482</td>\n",
       "      <td>8784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2672</td>\n",
       "      <td>1777</td>\n",
       "      <td>4500</td>\n",
       "      <td>8646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1231</td>\n",
       "      <td>682</td>\n",
       "      <td>2026</td>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "device_type  android  desktop_web   ios  mobile_web\n",
       "day                                                \n",
       "5               1463          895  2384        5149\n",
       "6               2870         2007  4337        8842\n",
       "7               2854         1600  4217        9531\n",
       "8               2729         1958  4373        8903\n",
       "9               2744         1712  4380        8764\n",
       "10              2562         1866  4482        8784\n",
       "11              2672         1777  4500        8646\n",
       "12              1231          682  2026        4040"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "device_type_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "e803c5fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'COUNT ')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Device_type by total count per day', size=16, y=0.95, weight='bold')\n",
    "\n",
    "device_type_1.plot(ax=ax, grid=True, cmap='tab10')\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('COUNT ', fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "565a9fff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8587794090>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Day wise movement on Device_Type category', size=16, y=0.95, weight='bold')\n",
    "\n",
    "device_type_1.plot(ax=ax, legend=True, grid=True, logy=True, cmap='tab10')\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('Log (COUNT) ', fontsize=16)\n",
    "plt.legend(loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a2584ba",
   "metadata": {},
   "source": [
    "## Event_Page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "229ba8a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "event_page = df.groupby(['event_page'])['day'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "965bafd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "event_page_1 = event_page.unstack(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "6b31a567",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>event_page</th>\n",
       "      <th>book_page</th>\n",
       "      <th>driver_page</th>\n",
       "      <th>search_page</th>\n",
       "      <th>splash_page</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1977</td>\n",
       "      <td>965</td>\n",
       "      <td>3995</td>\n",
       "      <td>2954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3548</td>\n",
       "      <td>1823</td>\n",
       "      <td>7219</td>\n",
       "      <td>5466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3576</td>\n",
       "      <td>1871</td>\n",
       "      <td>7307</td>\n",
       "      <td>5448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3572</td>\n",
       "      <td>1794</td>\n",
       "      <td>7221</td>\n",
       "      <td>5376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3586</td>\n",
       "      <td>1755</td>\n",
       "      <td>6979</td>\n",
       "      <td>5280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3424</td>\n",
       "      <td>1689</td>\n",
       "      <td>7201</td>\n",
       "      <td>5380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3506</td>\n",
       "      <td>1768</td>\n",
       "      <td>7137</td>\n",
       "      <td>5184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1639</td>\n",
       "      <td>801</td>\n",
       "      <td>3174</td>\n",
       "      <td>2365</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "event_page  book_page  driver_page  search_page  splash_page\n",
       "day                                                         \n",
       "5                1977          965         3995         2954\n",
       "6                3548         1823         7219         5466\n",
       "7                3576         1871         7307         5448\n",
       "8                3572         1794         7221         5376\n",
       "9                3586         1755         6979         5280\n",
       "10               3424         1689         7201         5380\n",
       "11               3506         1768         7137         5184\n",
       "12               1639          801         3174         2365"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(type(event_page_1))\n",
    "event_page_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4fe26f9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'COUNT ')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Events_Page by total count per day', size=16, y=0.95, weight='bold')\n",
    "\n",
    "event_page_1.plot(ax=ax, grid=True, cmap='tab10')\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('COUNT ', fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "db20dcf1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fig,ax = plt.subplots(1, figsize=(12,8))\n",
    "fig.suptitle('Day wise movement on Events_Page category', size=16, y=0.95, weight='bold')\n",
    "\n",
    "event_page_1.plot(ax=ax, grid=True, cmap='tab10')\n",
    "ax.set_yscale('log')\n",
    "\n",
    "ax.set_xlabel('DAY', fontsize=16)\n",
    "ax.set_ylabel('Log (COUNT) ', fontsize=16)\n",
    "plt.legend(loc='upper right')\n",
    "\n",
    "ax.tick_params(axis ='x', which ='both', length = 0)\n",
    "y_major=MultipleLocator(100)\n",
    "ax.yaxis.set_major_locator(y_major)\n",
    "\n",
    "# ax.set_yticklabels(['']*len(ax.get_yticklabels()))\n",
    "# y_major = MultipleLocator(10**3)\n",
    "# ax.yaxis.set_major_locator(y_major)\n",
    "\n",
    "# ax.yaxis.set_minor_locator(y_minor)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71224183",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0e91b1b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "newenv",
   "language": "python",
   "name": "newenv"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}